Summary

Dataset 1

Experiments excluded

Mask

Get figure file: figures/preliminary_dset-1_figure-mask.png

Peak coordinates

Get figure file: figures/preliminary_dset-1_figure-static.png
Get figure file: figures/preliminary_dset-1_figure-legend.png

Explorer

Meta-Analysis

Estimator

Parameters use to fit the meta-analytic estimator.

Corrector

Parameters use to fit the corrector.

Corrected meta-analytic map: z_corr-FDR_method-indep

Explorer

The following figure provides an interactive window to explore the meta-analytic map in detail.

Slice viewer

This panel shows the the corrrected meta-analytic map.

Get figure file: figures/corrector_figure-static.png

Diagnostics

Target image: z_corr-FDR_method-indep

Significant clusters

    X Y Z Peak Stat Cluster Size (mm3)
Tail Cluster ID          
Positive 1 -8.00 -56.00 30.00 7.38 11728
1a 0.00 -56.00 42.00 4.89
1b -6.00 -54.00 18.00 4.60
1c 8.00 -56.00 24.00 2.41
2 0.00 54.00 24.00 6.47 39056
2a -4.00 52.00 4.00 6.47
2b -2.00 54.00 28.00 6.21
2c -6.00 46.00 2.00 6.21
3 -50.00 -62.00 28.00 5.94 7944
3a -50.00 -56.00 22.00 4.89
3b -50.00 -52.00 30.00 3.39
3c -46.00 -58.00 38.00 3.07
4 -42.00 24.00 -8.00 5.42 14568
4a -50.00 24.00 -4.00 4.60
4b -46.00 20.00 -12.00 4.30
4c -50.00 10.00 24.00 4.30
5 -42.00 0.00 48.00 5.16 4616
5a -44.00 8.00 50.00 3.70
5b -36.00 -10.00 52.00 2.75
5c -34.00 -4.00 42.00 2.06
6 54.00 -32.00 2.00 4.89 9952
6a 48.00 -28.00 -4.00 4.60
6b 54.00 -20.00 -4.00 4.60
6c 50.00 -30.00 -2.00 4.60
7 50.00 -64.00 -2.00 4.30 11032
7a 22.00 -80.00 -10.00 4.00
7b 50.00 -64.00 -6.00 4.00
7c 22.00 -82.00 -4.00 3.70
8 34.00 24.00 -6.00 4.00 7888
8a 30.00 22.00 2.00 3.70
8b 52.00 26.00 8.00 3.39
8c 44.00 24.00 -4.00 3.39
9 -48.00 -34.00 44.00 4.00 1784
10 8.00 8.00 4.00 3.70 7680
10a 8.00 12.00 -10.00 3.07
10b -6.00 10.00 0.00 3.07
10c 14.00 12.00 6.00 3.07
11 -56.00 -32.00 -2.00 3.70 8024
11a -56.00 -26.00 4.00 3.70
11b -56.00 -38.00 0.00 3.39
11c -56.00 -26.00 -4.00 3.39
12 -50.00 4.00 -32.00 3.07 616
13 42.00 4.00 38.00 3.07 840
13a 44.00 6.00 30.00 2.41
13b 44.00 8.00 38.00 2.41
13c 44.00 10.00 26.00 2.06
14 -42.00 -78.00 -2.00 3.07 3056
14a -36.00 -76.00 -10.00 3.07
14b -42.00 -82.00 -6.00 2.75
14c -34.00 -76.00 -14.00 2.75
15 20.00 -6.00 50.00 2.41 536
15a 26.00 -2.00 54.00 2.06
15b 22.00 -12.00 52.00 1.71
16 46.00 -6.00 50.00 2.41 536
16a 44.00 2.00 48.00 2.06
16b 48.00 -6.00 54.00 2.06
16c 50.00 -6.00 46.00 2.06
17 46.00 -38.00 48.00 2.41 328
18 26.00 -48.00 -12.00 2.41 88
19 -58.00 -40.00 26.00 2.06 168
20 -56.00 -4.00 -16.00 2.06 88
21 -22.00 52.00 12.00 2.06 112
22 -4.00 -74.00 8.00 2.06 184
22a -4.00 -78.00 0.00 1.71
23 -8.00 -90.00 8.00 2.06 104
24 46.00 16.00 -28.00 2.06 112
25 -50.00 -74.00 2.00 2.06 152
26 -6.00 34.00 34.00 1.71 80
27 -10.00 -12.00 6.00 1.71 96
28 62.00 -8.00 -18.00 1.71 152

Label map: positive tail

Get figure file: figures/diagnostics_tail-positive_figure.png

FocusCounter

The FocusCounter analysis characterizes the relative contribution of each experiment in a meta-analysis to the resulting clusters by counting the number of peaks from each experiment that fall within each significant cluster.

The heatmap presents the relative contributions of each experiment to each cluster in the thresholded map. There is one row for each experiment, and one column for each cluster, with column names being PostiveTail/NegativeTail indicating the sign (+/-) of the cluster's statistical values. The rows and columns were re-ordered to form clusters in the heatmap.

Heatmap: positive tail

Methods

We kindly ask to report results preprocessed with this tool using the following boilerplate.

A multilevel kernel density (MKDA) meta-analysis \citep{wager2007meta} was performed was performed
with NiMARE 0.6.1 (RRID:SCR_017398; \citealt{Salo2023}), using a(n) MKDA kernel. An MKDA kernel
\citep{wager2007meta} was used to generate study-wise modeled activation maps from coordinates. In
this kernel method, each coordinate is convolved with a sphere with a radius of 10.0 and a value of
1. For voxels with overlapping spheres, the maximum value was retained. Summary statistics (OF
values) were converted to p-values using an approximate null distribution. The input dataset
included 2050 foci from 278 experiments. False discovery rate correction was performed with the
Benjamini-Hochberg procedure \citep{benjamini1995controlling}.

Bibliography

@article{Salo2023,
  doi = {10.52294/001c.87681},
  url = {https://doi.org/10.52294/001c.87681},
  year = {2023},
  volume = {3},
  pages = {1 - 32},
  author = {Taylor Salo and Tal Yarkoni and Thomas E. Nichols and Jean-Baptiste Poline and Murat Bilgel and Katherine L. Bottenhorn and Dorota Jarecka and James D. Kent and Adam Kimbler and Dylan M. Nielson and Kendra M. Oudyk and Julio A. Peraza and Alexandre Pérez and Puck C. Reeders and Julio A. Yanes and Angela R. Laird},
  title = {NiMARE: Neuroimaging Meta-Analysis Research Environment},
  journal = {Aperture Neuro}
}
@article{benjamini1995controlling,
  title={Controlling the false discovery rate: a practical and powerful approach to multiple testing},
  author={Benjamini, Yoav and Hochberg, Yosef},
  journal={Journal of the Royal statistical society: series B (Methodological)},
  volume={57},
  number={1},
  pages={289--300},
  year={1995},
  publisher={Wiley Online Library},
  url={https://doi.org/10.1111/j.2517-6161.1995.tb02031.x},
  doi={10.1111/j.2517-6161.1995.tb02031.x}
}
@article{wager2007meta,
  title={Meta-analysis of functional neuroimaging data: current and future directions},
  author={Wager, Tor D and Lindquist, Martin and Kaplan, Lauren},
  journal={Social cognitive and affective neuroscience},
  volume={2},
  number={2},
  pages={150--158},
  year={2007},
  publisher={Oxford University Press},
  url={https://doi.org/10.1093/scan/nsm015},
  doi={10.1093/scan/nsm015}
}